Energy-efficient hardware data prefetching

  • Authors:

  • Yao Guo;Pritish Narayanan;Mahmoud Abdullah Bennaser;Saurabh Chheda;Csaba Andras Moritz

  • Affiliations:

  • School of Electronics Engineering and Computer Science, Peking University, Beijing, China;University of Massachusetts, Amherst, MA;Kuwait University, Safat, Kuwait;BlueRISC Inc., San Jose, CA;University of Massachusetts, Amherst, MA and BlueRISC Inc., Amherst, MA

  • Venue:
  • IEEE Transactions on Very Large Scale Integration (VLSI) Systems
  • Year:
  • 2011

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Abstract

Extensive research has been done in prefetching techniques that hide memory latency in microprocessors leading to performance improvements. However, the energy aspect of prefetching is relatively unknown. While aggressive prefetching techniques often help to improve performance, they increase energy consumption by as much as 30% in the memory system. This paper provides a detailed evaluation on the energy impact of hardware data prefetching and then presents a set of new energy-aware techniques to overcome prefetching energy overhead of such schemes. These include compiler-assisted and hardware-based energy-aware techniques and a new power-aware prefetch engine that can reduce hardware prefetching related energy consumption by 7-11×. Combined with the effect of leakage energy reduction due to performance improvement, the total energy consumption for the memory system after the application of these techniques can be up to 12% less than the baseline with no prefetching.